EP2947799B1 - Verfahren zur im weiteren sinne linearen turboentzerrung in einem system mit mehreren nutzern und für einen mehrantennen-empfänger - Google Patents

Verfahren zur im weiteren sinne linearen turboentzerrung in einem system mit mehreren nutzern und für einen mehrantennen-empfänger Download PDF

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EP2947799B1
EP2947799B1 EP15168970.0A EP15168970A EP2947799B1 EP 2947799 B1 EP2947799 B1 EP 2947799B1 EP 15168970 A EP15168970 A EP 15168970A EP 2947799 B1 EP2947799 B1 EP 2947799B1
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signal
received signal
equalization
turbo
block
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EP2947799A1 (de
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Antonio CIPRIANO
Olivier GOUBET
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Thales SA
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Thales SA
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03012—Arrangements for removing intersymbol interference operating in the time domain
    • H04L25/03019—Arrangements for removing intersymbol interference operating in the time domain adaptive, i.e. capable of adjustment during data reception
    • H04L25/03057—Arrangements for removing intersymbol interference operating in the time domain adaptive, i.e. capable of adjustment during data reception with a recursive structure
    • H04L25/03076—Arrangements for removing intersymbol interference operating in the time domain adaptive, i.e. capable of adjustment during data reception with a recursive structure not using decision feedback
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0047—Decoding adapted to other signal detection operation
    • H04L1/0048—Decoding adapted to other signal detection operation in conjunction with detection of multiuser or interfering signals, e.g. iteration between CDMA or MIMO detector and FEC decoder
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/02—Arrangements for detecting or preventing errors in the information received by diversity reception
    • H04L1/06—Arrangements for detecting or preventing errors in the information received by diversity reception using space diversity
    • H04L1/0618—Space-time coding
    • H04L1/0631—Receiver arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03159—Arrangements for removing intersymbol interference operating in the frequency domain
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03891—Spatial equalizers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03891—Spatial equalizers
    • H04L25/03961—Spatial equalizers design criteria
    • H04L25/03968—Spatial equalizers design criteria mean-square error [MSE]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/06—Dc level restoring means; Bias distortion correction ; Decision circuits providing symbol by symbol detection
    • H04L25/067—Dc level restoring means; Bias distortion correction ; Decision circuits providing symbol by symbol detection providing soft decisions, i.e. decisions together with an estimate of reliability
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/01—Equalisers

Definitions

  • the field of the invention is that of digital radio communication systems and more particularly the multi-channel communication receivers, that is to say comprising several receiving antennas.
  • the invention also relates to multi-user systems in which the communication resources are shared between several users who can communicate simultaneously by sharing frequency bands or time slots.
  • the invention relates to all multi-user communication systems in which high levels of interference are generated both between transmitters associated with different users but also between the symbols conveyed by a signal transmitted by a user in that disturbances inherent to the propagation channel.
  • the invention specifically concerns the field of signal equalization in a multi-user context and also the field of turbo-equalization which consists in the iteration of the equalization and decoding functions in the objective final to improve the bit error rate or the packet error rate on the decoded symbols.
  • the invention finds particular application in cellular communication systems such as the 3GPP LTE system.
  • the invention particularly aims to design a turbo-equalizer based on a linear equalization filter in the broad sense.
  • a linear equalization filter in the broad sense.
  • Such a filter has the property of separately processing the real part and the imaginary part of the signal so as to make the best use of all the information contained in the signal in order to improve the equalization performance.
  • a linear equalizer in the broad sense has improved performance more particularly for signals modulated from a real constellation or a complex constellation having the non-circularity property.
  • the invention also relates to a method of equalization in the frequency domain and which is adapted to a multi-user context.
  • the invention proposes, in order to improve known equalization methods, a linear equalization method in the broad sense that aims to remove interference between multiple users that applies in the frequency domain.
  • the invention is particularly advantageous when the signal is modulated with the aid of a real constellation, which implies that the pseudo-correlation matrix of the signal is non-zero and can be exploited to improve the equalization filter.
  • the wide linear filtering step comprises filtering said complex correction signal by a first equalizing filter and the complex correction signal conjugated by a second equalizing filter.
  • the wide linear filtering step comprises filtering said complex correction signal by an equalizing filter and said equalization method further comprises a step of extracting the real part of each value. of the equalized signal converted into the time domain.
  • the wide linear filtering step comprises filtering said complex correction signal by an equalizing filter and said equalizing method further comprises a step of extracting, alternatively, the real part or the imaginary part of each successive value of the equalized signal converted into the time domain.
  • the invention also relates to the use of the method for equalizing a received signal or the turbo-equalization method according to the invention applied to a signal modulated according to an actual constellation, for example a constellation of the BPSK or M-PAM type. .
  • the invention also relates to the use of the method of equalizing a received signal or the turbo-equalization method according to the invention applied to a signal modulated according to an alternately real or imaginary constellation, for example a constellation of the type ⁇ / 2-BPSK or ⁇ / 2-M-PAM.
  • the subject of the invention is also a computer program comprising instructions for executing the method of equalizing a received signal or the turbo-equalization method according to the invention, when the program is executed by a processor and a receiver having a plurality of antenna elements for receiving a signal transmitted by a plurality of transmitters and a processor configured to execute the equalization method of a received signal or the turbo-equalization method according to the invention.
  • Variables designated by a lowercase letter in bold, such as x denote a vector
  • Variables designated by a capital letter in bold, such as X denote a matrix
  • F M is the Fourier transform matrix of size MxM, the input k, l of this matrix is equal to F M k , l of this matrix
  • mapping will be used to designate the transformation of one or more bits to a symbol of the constellation of the modulation used to format the signal.
  • mapping will be used to designate the inverse transformation to the mapping operation, namely the transformation of a modulated symbol into one or more bits according to the constellation used.
  • soft mapping designates the mapping operation when it is executed for so-called soft bits, otherwise called bits represented by a non-binary value, typically between 0 and 1 which is characteristic of their probability of likelihood.
  • the expression soft demapping designates the operation inverse to the soft mapping operation.
  • the figure 1 schematizes the communications system considered by the invention. It is a multi-user wireless transmission system comprising a plurality of transmitters 10 1 , ... 10 K each transmitting a radio signal to the same receiver 20 which is provided with a plurality of antennas A 1 , ... A Nr , with Nr the number of antennas at least equal to 1.
  • the transmitters 10 1 , ... 10 K each transmit a signal in operation the same time and frequency resources which generates interference between users from the point of view of the receiver 20. K is equal to the number of transmitters or users.
  • the system described in figure 1 is usually designated by distributed Multiple Input Multiple Output (MIMO) system.
  • MIMO distributed Multiple Input Multiple Output
  • the figure 2 describes a transmitter example 10k supports the system targeted by the invention. It should be noted that the invention specifically relates to an equalization method implemented by a receiver 20 and does not include steps performed by a transmitter. However, the type of transmitter envisaged is described solely by way of example and this to facilitate the general understanding of the invention. The features presented on the figure 2 may be made optional in part and more generally described transmitter can be replaced by other types of transmitters.
  • the transmitter 10 k receives as input bits of information which are coded with an error correction coder 11 which may be a convolutional code, a turbo code, an LDPC code or any other code for which there exists a decoding algorithm that produces soft information, i.e. non-binary information.
  • the bits encoded at the output of the encoder 11 are interleaved with an interleaver 12 k which may be different for each transmitter 10 1 , ... 10 K.
  • the interleaved bits are then modulated by a modulator 13k which may be different from one user to another.
  • the modulator 13 k outputs symbols belonging to a given constellation defined according to the type of modulation chosen.
  • the invention has improved performance, particularly for real constellations, ie for which the modulated symbols have a zero imaginary part.
  • the invention makes it possible to obtain improved results with respect to known linear equalization techniques when the constellation used for the modulation of the transmitted signal has a so-called non-circularity property.
  • the non-circularity property is expressed formally by the fact that if s ( n ) is a random symbol of the constellation emitted at time n, then the expectation of this squared symbol is different from zero E [ s 2 ( n )] ⁇ 0.
  • the quantity E [ s 2 ( n )] is also called pseudo-covariance in the literature. This property also extends to sampled or continuous signals. For vectors representing a portion of a signal, the pseudo-correlation is written E [ ss T ]. The invention is advantageously applied when this pseudo-correlation has a non-zero value.
  • Real constellations also called rectilinear (real-valued) constellations such as Binary Phase Shift Keying (BPSK) modulation, or Pulse Amplitude Modulation (PAM) amplitude modulations
  • BPSK Binary Phase Shift Keying
  • PAM Pulse Amplitude Modulation
  • the invention can also be applied to real constellations periodically rotated like the ⁇ / 2-BPSK, which alternates on each modulated symbol a conventional BPSK constellation ⁇ +1, -1 ⁇ and a BPSK constellation rotated by ⁇ / 2 radians ⁇ + not a word ⁇ .
  • the invention can also be applied to constellations called quasi-rectilinear, that is to say constellations whose symbols can be obtained by complex filtering of a signal described by the symbols of a real constellation.
  • modulations are Minimum Shift Keying (MSK), Gaussian Minimum Shift Keying (GMSK), Continuous Phase Modulation (CPM) continuous phase modulations with Binary Alphabet, or Offset Quadrature Amplitude Modulation (OQAM).
  • MSK Minimum Shift Keying
  • GMSK Gaussian Minimum Shift Keying
  • CPM Continuous Phase Modulation
  • OFDM Offset Quadrature Amplitude Modulation
  • the invention can also be applied to non-circular complex symbols, such as, for example, rectangular QAM constellations which have no circular symmetry (for example 8-QAM).
  • the invention is advantageously applied to modulations which have the property of non-circularity.
  • the invention can also be applied to modulations that do not have this property but in this case the improvement of the equalization performance will be negligible.
  • the modulated symbols are then transmitted to a framing block 14 which organizes the block data in a frame and can also insert pilot sequences which will be used, for example, at the receiver for the estimation of the channel.
  • the pilot sequences are generated by a module 15.
  • the block 14 implements a method of partial periodization of the data blocks, which allows the receiver to implement an equalizer in the frequency domain.
  • the block 14 may set up Orthogonal Frequency Division Multiplexing (OFDM) modulation with a total of N subcarriers including M subcarriers used with a CP prefix and possibly a cyclic suffix CS.
  • OFDM Orthogonal Frequency Division Multiplexing
  • Block 14 can implement a Single Carrier-Frequency Division Multiple Access (SC-FDMA) modulation, with M the number of subcarriers used for precoding with a Discrete Fourier Transform (DFT).
  • DFT Discrete Fourier Transform
  • N M
  • the transmitter implements a single carrier signal (Single Carrier - SC).
  • the transmitter also has an RF analog channel 16 for shaping the signal for transmission by radio.
  • This chain 16 introduces imbalances between the channel in phase I and the quadrature channel Q which leads to the output of block 16 a signal which is non-circular. If the imbalances I, Q are known on reception, then the invention can also be applied to this type of signal even if the modulation used does not have the property of non-circularity.
  • the figure 3 describes the overall functional structure of a wide linear receiver according to the invention.
  • Such a receiver 300 implements an iterative Interference Cancellation (IC) algorithm whose purpose is to suppress as much as possible the Inter-Symbol Interference also designated by ISI interference and the multi-user interference (Multi- User Interference - MUI) also referred to as MUI interference.
  • IC Inter-Symbol Interference
  • MUI multi-user interference
  • the algorithm implements in the iterations a linear filtering in the broad sense, which makes it possible to discriminate the signals received from two transmitters even with a single antenna.
  • the inter-symbol interference is generated when the signal symbols of the user of interest pass through a multi-path (frequency-selective) channel.
  • the MUI interference is generated by the signals of other users that are transmitted in the same time-frequency resources and are superimposed on the signal of the user of interest in a non-orthogonal manner. This is because, although user signals are transmitted by different antennas, in general there is no perfect spatial separation, except in very special cases.
  • the figure 3 represents a block diagram with the functional view of the receiver 300 in the case where the transmitted signals are obtained with a so-called SC-FDMA technique with CP prefix insertion. It is assumed here that the signals of the transmitters are synchronized to the receiver with a precision less than the duration of the CP prefix and that a synchronization algorithm has provided the synchronization instant to the receiver.
  • the signals are received by the different antennas A 1 , ... A NR of the receiver and are formatted into data blocks. On each reception channel, data blocks are extracted and then a step S 1 ,... S NR deletion of the prefix CP is executed.
  • the data blocks from the receiver antennas are then passed through a fast N FFT 1 , ... FFT NR , (Fast Fourier Transform - FFT) transform step in order to convert the time domain signals to the domain. frequency. Then the sample blocks at the output of the FFTs go into blocks D 1 ,... D NR which operate a selection of the inputs corresponding to the subcarriers actually occupied by the wanted signal.
  • the users use the same M subcarriers, in other words, only the useful signals allocated to the M subcarriers used are recovered at this stage and the unused subcarriers are deleted.
  • the pilot sequences are extracted from the signals coming from the reception antennas and sent to the block 110 which makes an estimate of the response of the channels and the variance of the noise.
  • the step executed by block 110 also provides an estimate of the variance of the thermal noise on each receiving antenna or the average of all these variances. In the following we use the second hypothesis.
  • the estimate of the MIMO channel H and the variance of the noise is then passed to the block 101 which carries out a step of calculating the equalizer and parameters related to soft demapping.
  • E AP [ ⁇ ] is the average conditioned on all prior information from the decoders and computed during the previous iteration.
  • the quantities E AP [ s k ] and ⁇ ⁇ k 2 are provided at block 101 by modules 102 1 , ... 102 K of flexible mapping which will be described later.
  • the receiver 300 performs iterative processing.
  • IC deletion Interference
  • Each vector z k corresponding to a transmitter is then sent to a module 103 1 , ... 103 K soft demapping, which produces flexible metrics for each bit that are related to the probability that the bit is 0 or 1.
  • This module of soft demapping takes different forms according to the statistics of the signal after equalization: if the starting constellation is real one can use a demapper for symmetric complex Gaussian statistics, otherwise a demapper for Gaussian statistics with non-zero pseudo-covariance is more suitable .
  • the flexible metrics are then deinterleaved by a de-interleaver 104 1 , ... 104 K which is the inverse block of the interleaver 12 k employed by an issuer. Then, when all the bits of a data packet are retrieved, the soft metrics are sent to a decoder 105 1 ,... 105 K which produces estimates of the bits sent and extrinsic information EXT which measures the probability that the bits be 0 and 1 but after decoding the error correcting code by removing the influence of the equalizer.
  • the EXT extrinsic information is then sent to the interleaver 112 k of the user k to be interleaved.
  • the extrinsic EXT interleaved information enters a flexible mapping module 102 k which calculates for each block the soft estimates of the emitted symbols E AP [ s k ], and the estimate of the average variance of the emitted symbols ⁇ ⁇ k 2 .
  • the outputs of blocks 112 k are sent to blocks 100 and 101 to start a new iteration.
  • the steps of equalization 100 and decoding 105 1 , ... 105 K are iterated a predetermined number of times.
  • the figure 4 illustrates this first variant of implementation of the turbo equalization module 100.
  • the turbo-equalization module 100 implements, according to the invention, the method of turbo linear equalization broadly in frequency on the signals coming from the N R antennas of the receiver.
  • the turbo-equalization block 100 aims to erase the MUI interference and the ISI interference and to equalize the signals in the spatio-frequency domain.
  • a first implementation of the block 100 consists of applying an equalizer 100 1.1 ... 100 K, M to each received signal symbol on each of the M useful frequency sub-carriers and K transmitters transmitting a signal to the receiver simultaneously as represented to the figure 4 .
  • Each equalizer 100 k, m is composed of two main functions, a first function 203 k, m suppression of the interference and a second function 204 k, m linear filtering in the broad sense of the frequency signal. This decomposition is represented in figure 5 .
  • E AP [ ⁇ ] be the average conditioned on all the prior information and E k, m [ ⁇ ] the conditioned average on all prior information except for the information relating to the th th symbol of the k th user. This corresponds to the fundamental intuition of the turbo processing according to which, in the treatment of a given symbol, it is not necessary to use the soft information coming from the previous iteration which concerns this same symbol.
  • E k, m ⁇ s k, m ⁇ 0 and E k, m [
  • 2 ] E s .
  • the vector e m + ( k -1) M is a column vector of size KM x 1 consisting of zeros with the exception of the index coefficient (m + (k-1) M) which is equal to 1.
  • the 203 k m interference suppression block outputs the vector r k, m from the input signal vector r, of the estimated matrix. of the channel H and the symbol estimates E AP [ s ] provided by the soft mapping modules 102 k .
  • the figure 6 shows in more detail the functions implemented by the block 203 k, m suppression of the interference.
  • This block executes neither more nor less the treatments represented by equation (1).
  • the estimate E AP [ s ] is multiplied by the vector e m + kM and the result of the multiplication is subtracted from the estimate E AP [ s ] to produce the vector E k, m [ s ] and then a inverse Fourier transform DFT 1 , ... DFT K is applied to each portion of the vector E k, m [ s ] corresponding to a user.
  • a step GSI of generating the interfering signals executes the multiplication of the outputs of the DFTs by the estimation matrix of channel H. The interfering signal obtained is finally subtracted from the received signal r.
  • the signal represented by the vector r k, m corresponds to the received signal from which the interference generated by all the symbols except the m-th symbol of the k-th user has been removed. It is then filtered via a step 204 k, m of linear filtering in the broad sense.
  • This filtering step is described in figure 7 .
  • the vector r k, m and its conjugate r * k, m are separately filtered by a multi-antenna filter 403 k, m linear in the broad sense from two equalizing filters g I, k, m and g Q, k, m .
  • g WL, k, m is a vector of size 2 N R M which represents the linear filter in the broad sense and which can also be described in an equivalent way by the two filters g , k, m and g Q, k, m of size N R M each.
  • the linear filter in the broad sense g WL, k, m therefore jointly processes the signal and its conjugate. Note also that this filter contains an inverse Fourier transform operation. The equalized symbols obtained at the output of this filter are therefore delivered in the time domain.
  • the turbo equalizer reconstructs the interfering signal which is given by the sum of the signals of the other users (interference MUI) and ISI interference reconstructed from the symbols of the user of interest minus the symbol that one wishes to decode. This reconstructed global interfering signal is then subtracted from the total signal. Then, the purified signal of the interference is passed through a frequency equalizer which further improves the separation between users and equalizes the residual ISI interference.
  • interfering signal which is given by the sum of the signals of the other users (interference MUI) and ISI interference reconstructed from the symbols of the user of interest minus the symbol that one wishes to decode.
  • This reconstructed global interfering signal is then subtracted from the total signal.
  • the purified signal of the interference is passed through a frequency equalizer which further improves the separation between users and equalizes the residual ISI interference.
  • FIGS. 4 to 7 illustrate the general principle of the equalizer according to the invention according to a first implementation for which an equalizing filter is applied to each symbol from each user.
  • the output of the equalizer filter can be expressed as the sum of the estimate of the useful signal weighted by the coefficient and of its conjugate weighted by the coefficient and the corrective signal filtered by the equalizer:
  • the block 200 instead of subtracting the MUI interference and the ISI interference of each user's useful symbol, the block 200 aims to subtract an estimate of the overall signal (more useful interference) in order to obtain a signal fix.
  • This corrective signal is then filtered by the wide linear filter block 201 to increase user separation and further reduce ISI interference.
  • the filtered corrective signal is then combined with the estimate of the useful signal obtained from the soft information at the output of the decoders at the previous iteration, so as to progressively improve (iteration after iteration) the estimate of the final useful signal .
  • the scheme of the figure 8 is functionally equivalent to the method described in figure 4 but allows a reduction in complexity due to the fact that the reconstruction of the signal received in the block 200 can be made by working in block with a fast Fourier transform. This is possible when the aim is to reconstruct the signal received in its entirety, in other words the useful signal and the interfering signal, but is no longer possible when the aim is to reconstruct the interfering signal alone, as is the case in the first variant. implementation described in Figures 4 to 7 .
  • the equalizer 100 comprises a first block 200 for generating N R corrective signals q 1 , .. q NR , a second block 201 for broadly linear filtering 201 of the corrective signals in order to produce a set of K corrected filtered signals y 1 , .. y K and a third block 202 for combining the filtered corrective signals with an estimated useful signal to produce a set of K equalized signals z 1 , .. z K.
  • the first block 200 subtracts from the signal received the reconstructed signal from the output information of the flexible mapping module. This first block 200 is described in figure 9 .
  • a module 300 then performs the following operations. The output vectors of the direct Fourier transforms are concatenated together, the concatenated vector is then multiplied by the channel estimation matrix H, and the output vector of size N R M is segmented into N R vectors of size M.
  • the signals at the output of the module 300 represent an estimate of the signals received from the symbols reconstructed using the outputs of the decoders. They therefore include MUI interference and ISI interference, ie all sources of interference, as well as the useful signal that is to be decoded.
  • the operations 301 1 ,... 301 NR perform an input-input subtraction between the received signals r 1 , .. r NR and the estimated signals at the output of the module 300.
  • the reconstructed signal at the output of the module 300 corresponds to the signals transmitted through the filters of the propagation channels. So the vectors q n will only represent noise.
  • the block 200 produces corrective signals q n which once filtered by the filter block 201 and summed to the soft estimates of the useful signals by the block 202 will allow the signals z k to gradually approach the useful signals actually transmitted (naturally within the limit of the noise present).
  • the second wide linear filter block 201 is described in FIG. figure 10 .
  • F M is the Fourier transform matrix defined in the preamble of the present description.
  • the vector q is then conjugated 403 input by input to obtain the vector q *.
  • the vectors q and q * are transmitted to the multi-antenna filtering unit 402 which performs the following operation:
  • the filtering performed is a linear filtering in the broad sense, that is to say that the vector q and its conjugate q * are filtered separately.
  • the vector Y of size equal to MK, is then segmented into K vectors Y k of sizes equal to M.
  • the matrix operation can be done efficiently because the matrices each have only N R MK inputs other than zero.
  • the number K of users is assumed to be known or a hypothesis is taken on this number.
  • the filtered vectors are converted in the time domain by means of K inverse Fourier transform modules IDFT 1 , ... IDFT K.
  • the structure of the figure 10 is a generic structure that can be applied to any type of constellation (real, quasi-rectilinear, complex).
  • the figure 11 describes a variant of implementation of the linear filtering module in the broad sense 201 in the case where the emitted signal is modulated with a real constellation.
  • the structure of the figure 10 can be optimized to perform the same function but with a limited number of operations.
  • This matrix J represents the inversion of the frequency axis of a discrete and periodic signal; it can be appreciated by applying a vector input and looking at the output. The multiplication by this matrix can be implemented by permutations.
  • the filter represented by the block diagonal matrix G I in the frequency domain has an impulse response in the time domain that can be expressed by a circulating matrix per block
  • the figure 12 describes the third block 202 of combining filtered corrective signals with an estimate of the useful signal.
  • the function of the block 202 is therefore to add to the corrected signals filtered at the output of the filtering unit 201 the estimates of the useful signals obtained from the soft information of the decoders calculated at the previous iteration and weighted by the estimates of the amplitudes ⁇ I, k and ⁇ Q, k .
  • the soft information from the decoders is zero.
  • the block 202 therefore has no effect at the first iteration of the method as the block 200 and the output of the filter block 201 is the estimated useful signals used.
  • the block 202 adds a noise term from the filtering 201.
  • the function of the block 202 is to improve the estimation of the useful signal by means of the corrective signal at the output of filtering 201.
  • the block 202 of combination with the estimates of the useful signals takes a simplified form as described in FIG. figure 13 .
  • the logical and functional description of block 202 is the same as for the general case of complex constellations.
  • the figure 14 describes the module 101 for calculating the coefficients of the equalizer according to a first embodiment applicable to complex constellations.
  • This module 101 comprises a first block 501 for calculating the equalizer in the frequency domain and for calculating an estimate of the amplitude of the useful symbols.
  • the module 101 also comprises a second block 502 for calculating the noise variance after equalization. More precisely, block 502 determines the covariances and pseudo-covariances of the signal after equalization. Its implementation is not developed here because it concerns calculation principles known to those skilled in the art.
  • the first block 501 calculates an equalizer according to the criterion of minimization of the mean square error called MMSE criterion.
  • MMSE minimization of the mean square error
  • the goal of this MMSE equalizer is to reduce MUI and ISI interference, if possible up to noise.
  • this equalizer uses the degrees of freedom it has at its frequency response to limit the ISI interference of each user. It also uses the spatial degrees of freedom, given by the number of antennas in reception, to limit the MUI interference and the degrees of freedom related to the statistical properties of the non-circular signals, to further limit the interference MUI.
  • C r k, m is the covariance matrix of r k, m and C r k, m s k, m is the vector of cross-covariance and cross-covariance of r k, m and m th symbol of the kth user s k, m.
  • ⁇ k , m 2 E AP
  • 2 ] for all ket m, and ⁇ s E k, m [ sk, m 2 ] for all indices k and m.
  • E s and ⁇ k , m 2 are real numbers and E s and ⁇ ⁇ k , m 2 are usually complex numbers.
  • the presence of multiple users is indicated by the matrix diag ⁇ ⁇ 0 2 , ... , ⁇ ⁇ K - 1 2 ⁇ I M which is of size KM x KM, and its corresponding for the matrix of pseudo-covariance, and by the matrix which is of size N R M x KM.
  • ⁇ ⁇ k 2 and ⁇ ⁇ ⁇ k 2 describe the influence of the soft information coming from the decoders on the expression of the equalizer. In particular, these values give the estimated variances and pseudo-variances of the emitted symbols.
  • ⁇ ⁇ k 2 E s
  • ⁇ ⁇ ⁇ k 2 E ⁇ s
  • the pseudo-covariance matrix is computed as a function of the pseudo-covariance ⁇ s of the transmitted symbols which is non-zero for modulations having a constellation satisfying the so-called non-circularity property as explained at the beginning. of the present description.
  • g I, k, m and g Q, k, m are vectors of size N R M which respectively filter the signals and their conjugates and constitute one of the outputs of block 501 for all k and all m.
  • the matrix ⁇ 1.1 represents the covariance matrix of the received signal r formed by the concatenation of the vectors r n at the input of the block 100.
  • ⁇ 1.1 E ⁇ r - E AP r r - E AP r H ⁇
  • E AP [] is the calculated expectation using the prior information from the decoders and computed during the previous iteration.
  • Covariance is a measure of the correlation between the variation of the signal with respect to its mean and the same conjugate variation.
  • the terms H in the correlation illustrate that the multi-antennal channel (between the users and the antennas of the receiver) introduces a correlation, a link between the received signals.
  • the covariance matrix of the received signal takes the following form
  • the pseudo-covariance is a measure of the correlation between the signal (without its mean, therefore the variation of the signal) with the same variation. Since a complex signal is formed of a real part and an imaginary part, thus of two random variables, two relations are needed to define the statistical behavior of a complex signal. Complex signals whose distribution has a central symmetry around the origin (so-called circularity), have a pseudo-covariance zero.
  • the pseudo-covariance matrix of the received signal depends on the pseudo-covariance ⁇ s of the transmitted symbols which is non-zero for modulations having a constellation satisfying the so-called non-circularity property as explained at the beginning. of the present description.
  • the covariance and pseudo-covariance matrices make it possible to completely characterize the second-order statistics of a complex signal.
  • the pseudo-covariance is zero.
  • the covariance and pseudo-covariance matrices calculated here make it possible to take into account the multi-user aspect.
  • index of the symbol m is omitted because it can be shown that this quantity is independent of the symbol index and depends only on the index of the user. So for the calculation we can choose any index m . Efficient ways to calculate these quantities exist, but they are not detailed here for the case of complex constellations. They will be for the case of real constellations.
  • the figure 15 presents the functional diagram of the calculation of the equalizer in the case of signals modulated by real constellations of M-PAM or BPSK type.
  • the constraint of real constellations makes it possible to simplify the realization of block 101.
  • the filter for the symbol m of the user k depends on the soft information through the matrix ⁇ , because this matrix contains the estimates of the covariances of the transmitted symbols, and through the factor 1+ ⁇ k , which is a normalization factor filter energy which also depends on the soft information from the decoders.
  • These factors ⁇ k are independent of the index m of the symbol and depend only on the user. This makes it possible to gather a filter per user by uniting the filters of all the symbols of the user considered.
  • BOY WUT WL , k E s 1 + ⁇ k ⁇ ⁇ - 1 H H * I K ⁇ J e K ⁇ F M
  • This filter which has a size of 2 N R M x M, can be suitably calculated using the property that the matrices have a diagonal block structure or the specific structure of the matrix J.
  • the matrix ( e K ⁇ F M ) represents the inverse transform (when the filter is applied) from the time domain to the frequency domain, and the other terms represent the actual frequency filter.
  • ( I K ⁇ F M ) indicates the inverse DFT set at the filter output.
  • ⁇ 1.1 H diag ⁇ ⁇ 1 2 , ... , ⁇ ⁇ k 2 , ... , ⁇ ⁇ K 2 ⁇ I M H H + ⁇ ⁇ I NOT R M
  • ⁇ s E s .
  • ⁇ 1.2 H diag ⁇ ⁇ 1 2 , ... , ⁇ ⁇ k 2 , ... , ⁇ ⁇ K 2 ⁇ J H T
  • ⁇ 1.1 is a diagonal matrix per block and that ⁇ 1.2 is a block matrix where each block has the structure of the matrix J. It will be said later that the matrix has a structure J by block.
  • the matrices of the equalizer can be calculated quickly because they are products of diagonal matrices by block or with structure J by block.
  • the coefficients of the equalizer G Q can be calculated from those of G I by simple conjugation and permutation. Indeed, in the case of real constellations, Only the matrix G I is therefore necessary.
  • Es is a design factor of the constellation of modulation used. It can be taken equal to 1.
  • the modulation step 13 k of the transmitted signal uses real constellations, for example M-PAM or BPSK, but a phase rotation of ⁇ / 2 is applied to all the even symbols of each user.
  • the framing function in this case uses a framing with prefix CP and possibly suffix CS.
  • the soft estimates which have real values in this variant embodiment, the odd indices of the input block are left unchanged, those of even index are multiplied by the imaginary unit j. This operation is carried out by block 17.
  • the remainder of block 200 operates as before. It is therefore in this case also to generate an estimate of the signals received from the different users from an estimate of the H channel and to subtract this estimate from the received signal to obtain a corrective signal.
  • the block 201 of linear filtering in the broad sense is also slightly modified in the context of the real constellations turned and is described again in figure 17 .
  • the input is filtered by a filter G I as in the case of real constellations (not turned) but with different coefficients.
  • a new block 412 alternating extraction must be added. This block jointly accomplishes the rotation of the symbols of the constellation and the correct combination that makes it possible to exploit the fact that the constellation of origin is real.
  • J M / 2 is a permutation of the identity matrix, an anti-diagonal of values at 1 begins at the input ( M / 2 + 1, 1) of the matrix.
  • J M / 2 has the same properties as the matrix J.
  • the multiplication by this matrix can be implemented by permutations.
  • the block 502 which calculates the variances of the noise after equalization remains unchanged compared to the case of real constellations.
  • Block 501 must have the following modifications.
  • the matrix ⁇ is written again in its generic form (14). Its sub-matrices take the following forms that allow to give an efficient way to implement the calculation of the covariance matrix and its inverse.
  • the matrix J M / 2 is defined in equation (29) and its application can be implemented by a simple permutation.
  • the matrix J M / 2 represents a translation of M / 2 samples in the frequency axis of a discrete and periodic signal.
  • ⁇ 1.2 H diag ⁇ ⁇ 1 2 , ... , ⁇ ⁇ k 2 , ... , ⁇ ⁇ K 2 , ⁇ J M / 2 H T
  • ⁇ 1.1 is a diagonal matrix per block and ⁇ 1.2 is a block matrix where each block has the structure of the matrix J M / 2 . It will be said later that the matrix has a structure J M / 2 per block.
  • the matrices S 1 and S 2 are subsequently calculated through formula (25), which can be implemented in a less complex manner thanks to the structure of the matrices in play.
  • the matrices S 1 and S 2 have the same properties as in the case of real constellations.
  • the matrices ⁇ 1 and ⁇ 2 are also calculated as in (27).
  • the matrix is applied to the signal thus showing the IDFT inverse Fourier transform F M H and the de-rotation diag ( ⁇ *).
  • G WL has the same structure as the filter in the case of real constellations with the matrix J M / 2 instead of J, the coefficients ⁇ k calculated with (31) and D is calculated as in (23).
  • G WL can also be expressed in the following form
  • the matrices of the equalizer can be computed quickly because they are products of diagonal matrices per block or with structure J M / 2 per block. Indeed, as explained above, in the case of actual constellations shot, Only the matrix G I is therefore necessary.
  • the Figures 18 and 19 illustrate the performances, in packet error rate, obtained thanks to the equalization method according to the invention.
  • the Figures 18 and 19 show the packet error rate in an ETU channel SC-FDMA system for a prior art linear turbo-equalizer with QPSK and convolution rate code 1/3 and for a linear turbo-equalizer in the broad sense according to the invention with 4-PAM and convolutional code of 1/3 rate.
  • the figure 18 shows the performances obtained with an antenna at the reception
  • the figure 19 shows the performance with two antennas at the reception.
  • the receiver uses five iterations and the received signals all have the same average power.
  • the curves referenced by L are those obtained with a linear turbo-equalizer according to the prior art.
  • the curves referenced by WL are those obtained with a linear broadband turbo-equalizer according to the invention.
  • K is the number of users, in other words the number of signals transmitted simultaneously.
  • Linear turbo-equalization with K 1 (single-user) and low signal-to-noise ratio has a gain on the wide-linear linear turbo-equalization which is due to the better form factor of the QPSK compared to the 4- WFP.
  • the linear turbo-equalizer can not support two users with an acceptable packet error rate (PER).
  • the broad linear turbo-equalizer according to the invention makes it possible to decode two users with a degradation of 3 dB compared to the linear case.
  • This gain is due to the implementation of the equalizer G I. This is due to formulas (25) where S 2 is non-zero. In case of linear receiver S 2 is zero because the pseudo-covariance matrix ⁇ 1.2 is imposed zero.
  • the proposed broad linear turbo-equalization method has a loss of signal to noise ratio of about 2 dB compared to the linear turbo-equalization method.
  • it manages to support more users than a standard linear receiver, including 4 users without significant performance degradation in terms of packet error rate.
  • the equalization method according to the invention can be implemented by software and / or hardware means. It can in particular be implemented as a computer program including instructions for its execution.
  • the computer program can be recorded on a processor-readable recording medium.
  • the turbo-equalizer according to the invention can in particular be implemented in the form of a processor which can be a generic processor, a specific processor, an integrated circuit specific to an application (also known by the English name ASIC for "Application-Specific Integrated Circuit") or a network of programmable gates in situ (also known by the English name of FPGA for "Field-Programmable Gate Array”).
  • a processor which can be a generic processor, a specific processor, an integrated circuit specific to an application (also known by the English name ASIC for "Application-Specific Integrated Circuit") or a network of programmable gates in situ (also known by the English name of FPGA for "Field-Programmable Gate Array”).

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Claims (11)

  1. Verfahren zum Entzerren eines von einer Vielzahl von Antennenelementen empfangenen Signals durch mindestens einen Entzerrfilter, wobei das empfangene Signal aus der Übertragung von Signalen stammt, die von einer Vielzahl von Sendern übertragen werden, wobei das Verfahren Folgendes umfasst:
    • einen Umwandlungsschritt des empfangenen Signals in dem Frequenzbereich,
    • einen Subtraktionsschritt (203k,m) einer Schätzung der Interferenz zwischen Symbolen und der Interferenz zwischen Benutzern von dem Signal, um ein komplexes Korrektursignal zu erlangen,
    • einen gemeinsamen linearen Filterungsschritt im weiteren Sinne (204k,m, 201) des komplexen Korrektursignals und des konjugierten komplexen Korrektursignals, um ein entzerrtes Signal zu erlangen,
    • einen Umwandlungsschritt des entzerrten Korrektursignals in dem Zeitbereich,
    • einen Berechnungsschritt der Kovarianzmatrix des empfangenen Signals,
    • einen Berechnungsschritt der Pseudokovarianzmatrix des empfangenen Signals mindestens ausgehend von der Pseudokovarianz der Symbole der übertragenen Signale,
    • einen Berechnungsschritt (101) der Koeffizienten des mindestens einen Entzerrfilters ausgehend von der Kovarianzmatrix und der Pseudokovarianzmatrix des empfangenen Signals.
  2. Verfahren zum Entzerren eines empfangenen Signals nach Anspruch 1, ferner umfassend:
    • einen Subtraktionsschritt (203k,m, 200) einer Schätzung des übertragenen Signals vom empfangenen Signal und
    • einen Schritt (202) zum Kombinieren des entzerrten Signals mit einer Schätzung des übertragenen Signals,
    • wobei der Schritt (204k, m, 201) des linearen Filters im weiteren Sinne konfiguriert ist, um ausgehend von einer Anzahl NR, die der Anzahl von Antennenelementen entspricht, komplexer Korrektursignale eine Anzahl K, die der Anzahl der übertragenen Signale entspricht, entzerrter komplexer Korrektursignale zu erzeugen.
  3. Verfahren zum Entzerren eines empfangenen Signals nach Anspruch 2, wobei der lineare Filterungsschritt im weiteren Sinne (201) die Filterung (402) des komplexen Korrektursignals durch einen ersten Entzerrfilter ( G I ) und des komplexen Korrektursignals, das durch einen zweiten Entzerrfilter ( G Q ) konjugiert wird, umfasst.
  4. Verfahren zum Entzerren eines empfangenen Signals nach Anspruch 2, wobei der lineare Filterschritt im weiteren Sinne (201) die Filterung (410) des komplexen Korrektursignals durch einen Entzerrfilter ( G I ) umfasst, und das Entzerrungsverfahren ferner einen Schritt (411) zum Extrahieren des tatsächlichen Teils von jedem Wert des umgewandelten entzerrten Signals in dem Zeitbereich umfasst.
  5. Verfahren zum Entzerren eines empfangenen Signals nach Anspruch 2, wobei der lineare Filterschritt im weiteren Sinne (201) die Filterung (410) des komplexen Korrektursignals durch einen Entzerrfilter ( G I ) umfasst und das Entzerrungsverfahren ferner einen Schritt (412) zum abwechselnden Extrahieren des tatsächlichen oder imaginären Teils von jedem nachfolgenden Wert des umgewandelten entzerrten Signals in dem Zeitbereich umfasst.
  6. Verfahren zum Entzerren eines empfangenen Signals nach einem der vorherigen Ansprüche, wobei der Berechnungsschritt (101) der Koeffizienten des Entzerrfilters mindestens Folgendes umfasst:
    • einen Teilschritt (501) zum Berechnen des Entzerrfilters in dem Frequenzbereich und zum Berechnen einer Schätzung der Amplitude der Symbole des übertragenen Signals,
    • einen Teilschritt (502) zum Berechnen der Kovarianzen und Pseudokovarianzen des Signals nach der Entzerrung.
  7. Verfahren zur Turboentzerrung eines empfangenen Signals, umfassend die iterative Ausführung der folgenden Schritte:
    • einen Ausführungsschritt des Verfahrens zum Entzerren eines empfangenen Signals nach einem der vorherigen Ansprüche,
    • einen Schritt (1031, ... 103K) zum Umwandeln des entzerrten Signals in demodulierte Bits,
    • einen Schritt (1051, ... 105K) zur Dekodierung der demodulierten Bits,
    • einen Schritt (1021, ... 102K) zum Umwandeln der dekodierten Bits in eine Schätzung des übertragenen Signals.
  8. Verwendung des Verfahrens zum Entzerren eines empfangenen Signals nach einem der Ansprüche 1 bis 6 oder des Turboentzerrungsverfahrens nach Anspruch 7, das auf ein gemäß einer tatsächlichen Konstellation moduliertes Signal angewendet wird, beispielsweise eine Konstellation vom Typ BPSK oder M-PAM.
  9. Verwendung des Verfahrens zum Entzerren eines empfangenen Signals nach einem der Ansprüche 1 bis 6 oder des Turboentzerrungsverfahrens nach Anspruch 7, das auf ein gemäß einer alternativ tatsächlichen oder imaginären Konstellation moduliertes Signal angewendet wird, beispielsweise eine Konstellation vom Typ n/2 BPSK oder n/2 M-PAM.
  10. Computerprogramm, umfassend Anweisungen zum Ausführen des Verfahrens zum Entzerren eines empfangenen Signals nach einem der Ansprüche 1 bis 6 oder des Turboentzerrungsverfahrens nach Anspruch 7, wenn das Programm von einem Prozessor ausgeführt wird.
  11. Empfänger mit einer Vielzahl von Antennenelementen zum Empfangen eines von einer Vielzahl von Sendern übertragenen Signals und einem Prozessor, der konfiguriert ist, um das Verfahren zum Entzerren eines empfangenen Signals nach einem der Ansprüche 1 bis 6 oder das Turboentzerrungsverfahren nach Anspruch 7 auszuführen.
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